AI Engineer

Charles Schwab Corporation; Austin (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

Charles Schwab Corporation in Austin, TX, is hiring an AI Engineer (individual contributor) to shape AI adoption across enterprise development. You will work at the intersection of developer experience, platform engineering, and applied AI to boost productivity and quality.

You’ll evaluate and operationalize AI tools, build reusable AI workflows, and collaborate with cross‑functional teams to embed AI into existing processes. Strong coding and communication skills are essential.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field or equivalent experience.
• 5+ years in software/platform/DevEx roles with modern delivery practices.
• Familiarity with NLP, CV, or generative AI models for use cases.
• Experience in reference architectures, standards, and guardrails across teams.
• Strong integration skills across delivery stack (SCM, CI/CD, containers, observability).
• Proven ability to influence leaders and drive adoption without authority.
• Proficient in Python; Java for backend integration is a plus.
• Knowledge of REST APIs and microservices for deploying AI models.
• Knowledge of AI trends and evaluation of tools (OpenAI, Copilot, etc.).
• Excellent written and verbal communication for docs and training.

Responsibilities

• Deliver AI-enabled solutions to raise product quality and developer productivity.
• Design and evolve AI solutions to support a broad STS developer base.
• Pilot and operationalize emerging AI developer tools for enterprise fit.
• Create reusable prompts, templates, and AI-augmented workflows.
• Act as a champion for AI-assisted development thru demos and forums.
• Collaborate with engineering, architecture, and platform teams.
• Produce clear technical documentation for adoption and onboarding.
• Contribute to training materials and internal communications.
• Use feedback to refine solutions and maximize value.
• Measure outcomes and refine standards to improve lead time for change.
• Evolve roadmap based on priorities and tech trends.

Skills

Python

REST APIs

AI/ML concepts

Applied AI

Documentation

Communication

Influence without authority

Education

Bachelor's degree in CS/Engineering or related field

Tools

GitHub Copilot

CI/CD tools

Kubernetes

GitHub Enterprise

Azure/AWS/GCP

Job description

Your Opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location.

Schwab Technology Services (STS) is investing in the integration of AI capabilities across the Software Development Life Cycle, and the AI Engineer (individual contributor) offers a unique opportunity to be part of that transformation from the outset. As a member of this team, you will help shape how AI is adopted and scaled across our enterprise development community, influencing modern engineering practices at a meaningful scale. You'll work at the intersection of developer experience, platform engineering, and applied AI, driving measurable improvements in productivity, quality, and engineering standards across the organization. This is a highly visible, hands‑on role that combines technical depth with enterprise-wide influence — ideal for engineers who are energized by enabling others, learning and passionate about the future of software delivery.

• Delivery of AI-enabled solutions that improve overall product quality, drive consistency in developer practices and significantly increase developer productivity across the organization
• Design, evolve, and enhance AI solutions to effectively support a diverse cross-section of STS developers, ensuring usability, scalability, and alignment with enterprise development standards
• Evaluate, pilot, and operationalize emerging AI developer tools (e.g., code assistants, AI-powered testing, automated code review) to determine enterprise fit, define rollout strategies, and manage adoption lifecycle
• Build and curate reusable prompts, templates, and AI-augmented workflows that lower the barrier to entry and help developers get productive with AI tools quickly
• Act as a visible champion for AI-assisted development, engaging with developer communities through demos, office hours, brown bags, and internal forums
• Partner closely with engineering, architecture, and platform teams to ensure AI capabilities are well-integrated into existing development workflows and toolchains
• Create and maintain clear, high-quality technical documentation to support solution adoption, onboarding, and long‑term sustainability
• Contribute to training programs, enablement materials, and internal communications to drive awareness, understanding, and effective usage of AI solutions
• Continuously evaluate feedback from developer communities and stakeholders to refine solutions and maximize business and technical value
• Establish ways to measure success and outcomes, and use data to refine standards, improve reliability, and accelerate lead time for change
• Continuously evolve the roadmap based on business priorities, team feedback, and changes in cloud, automation, AI-assisted delivery, and developer experience
• Responsible for operationalizing AI solutions developed by internal teams, integrating them into the developer environment, and supporting their enterprise‑wide deployment and maintenance

What you have

To ensure that we have fulfilled our promise of "challenging the status quo," this role has specific qualifications that successful candidates should have.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
• 5+ years in software engineering, platform engineering, or developer experience roles, with direct responsibility for modern software delivery practices
• Familiarity with NLP, computer vision, or generative AI models depending on use cases
• Demonstrated experience designing and socializing reference architectures, standards, and guardrails adopted across multiple teams or product lines
• Strong integration skills across delivery ecosystem components (source control, CI/CD, artifact management, container platforms, observability)
• Proven ability to influence engineering leaders and drive adoption across teams without direct authority
• Proficient in Python, and possibly Java for backend integration
• Knowledge of REST APIs and microservices for deploying AI models
• Stay current with trends, tools, and developments in the AI industry, including emerging models, platforms, and frameworks (e.g., OpenAI, Anthropic, GitHub Copilot, etc.), and evaluate their potential impact and applicability within the company's developer environment
• Excellent written and verbal communication skills, with the ability to create compelling documentation, training materials, and stakeholder presentations

Preferred Qualifications

• Experience with AI-assisted developer tools such as GitHub Copilot, Copilot Chat, Claude Code, Cursor, Amazon Q Developer, or similar - including configuring, customizing, and measuring their effectiveness at scale
• Experience building or scaling an internal developer platform (IDP), including self‑service workflows, golden paths, and developer experience measurement
• Experience designing secure and compliant delivery solutions in a regulated environment, including integration with identity management, secrets management, policy-as-code, vulnerability scanning, and audit automation
• Experience with cloud platforms in hybrid environments (AWS, Azure, or GCP) and Kubernetes‑based platforms
• Experience with GitHub Enterprise, GitHub Actions, Jenkins, Azure DevOps, Argo CD, Terraform, or similar at enterprise scale
• Experience with software supply chain security practices (SBOM, SLSA, provenance, signing, dependency governance)
• Experience implementing DORA metrics or similar delivery performance measurement frameworks
• Experience leading large‑scale migrations or toolchain consolidations with strong change management
• Familiarity with prompt engineering, RAG patterns in the context of enterprise developer tooling
• Familiarity with value stream management concepts and end‑to‑end delivery measurement
• Advanced degree or relevant certifications in cloud, security, or architecture
• Knowledge of prompt engineering and embedding based search

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.